Wearing detection method and system, intelligent wearable device and medium

Abstract

The invention provides a wearing detection method and system, intelligent wearable equipment and a computer readable storage medium, and belongs to the technical field of intelligent wearable device.The wearing detection method is applied to the intelligent wearable equipment, and breathing vibration signals of a user are collected in real time through a bone conduction microphone arranged on a nose pad; when the breathing vibration signal is larger than a preset first threshold value, it is judged that the intelligent wearable device is in a first state; the first state is a standard wearing state; when the breathing vibration signal is smaller than a preset first threshold value, it is judged that the intelligent wearable device is in a second state. According to the wearing detection method, the technical effect of greatly reducing the false triggering probability of wearing detection of the intelligent wearing equipment can be achieved.

Description

Technical Field

[0001] This invention belongs to the field of smart wearable device technology, specifically relating to a wear detection method, system, smart wearable device, and computer-readable storage medium. Background Technology

[0002] Smart wearable devices are experiencing rapid growth and are widely used in various fields such as health monitoring, personal entertainment, and professional medical care. In existing technologies, the wear detection function of smart wearable devices is generally implemented using capacitive sensors. However, for capacitive sensors that identify the user's wearing status by detecting changes in capacitance, while highly sensitive, they are also more susceptible to external interference; for example, hand contact or movement of the glasses can erroneously activate the wear detection function.

[0003] Therefore, there is an urgent need for a method and system for detecting wear to solve the problem of false triggering. Summary of the Invention

[0004] The present invention provides a wear detection method, system, smart wearable device, and computer-readable storage medium to overcome at least one technical problem existing in the prior art.

[0005] To achieve the above objectives, the present invention provides a wearing detection method, which is applied to a smart wearable device, the smart wearable device including a nose pad; the wearing detection method includes:

[0006] The user's breathing vibration signals are collected in real time using a bone conduction microphone; wherein, the bone conduction microphone is mounted on the nose pad.

[0007] When the breathing vibration signal is greater than a preset first threshold, the smart wearable device is determined to be in a first state; the first state is the standard wearing state.

[0008] When the breathing vibration signal is less than a preset first threshold, the smart wearable device is determined to be in the second state.

[0009] Furthermore, a preferred method is that the second state is a non-wearing state.

[0010] Furthermore, a preferred method is to further include, after acquiring the user's breathing vibration signal in real time using the bone conduction microphone, performing filtering preprocessing on the breathing vibration signal to filter out breathing vibration signals with frequencies higher than 10 Hz.

[0011] Furthermore, a preferred method further includes, after filtering and preprocessing the respiratory vibration signal, performing signal amplification processing on the respiratory vibration signal.

[0012] Furthermore, a preferred method is that, after determining that the smart wearable device is in the first state, the control module in the smart wearable device controls the speaker in the smart wearable device to emit audio signals and / or controls the smart wearable device to receive voice call signals.

[0013] Furthermore, a preferred method is to determine that the smart wearable device is in a third state when the breathing vibration signal is less than a preset first threshold and greater than a preset second threshold.

[0014] The third state is a non-standard wearing state.

[0015] Furthermore, a preferred method is to determine that the smart wearable device is in a fourth state when the breathing vibration signal is less than a preset second threshold.

[0016] When the duration of the smart wearable device in the fourth state exceeds a preset first time threshold,

[0017] The control module in the smart wearable device controls the speaker in the smart wearable device to stop emitting audio signals and / or controls the smart wearable device to stop receiving voice call signals.

[0018] Furthermore, a preferred method is that the first threshold is an amplitude of 0.5V and the second threshold is an amplitude of 0.1V.

[0019] To address the aforementioned issues, the present invention also provides a wear detection system, comprising a signal acquisition unit for real-time acquisition of a user's respiratory vibration signals using a bone conduction microphone; wherein the bone conduction microphone is mounted on the nose pad of the smart wearable device;

[0020] The wearing status determination unit is used to determine that the smart wearable device is in a first state when the breathing vibration signal is greater than a preset first threshold; the first state is the standard wearing state.

[0021] When the breathing vibration signal is less than a preset first threshold, the smart wearable device is determined to be in the second state.

[0022] To address the aforementioned problems, the present invention also provides a smart wearable device, the smart wearable device including a memory, a processor, and a wear detection program stored in the memory and executable on the processor, wherein the wear detection program, when executed by the processor, implements the steps of the wear detection method described above.

[0023] To address the aforementioned problems, the present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the wear detection method described above.

[0024] This invention discloses a wear detection method, system, electronic device, and storage medium. The wear detection method is applied to a smart wearable device, which uses a bone conduction microphone mounted on the nose pad to collect the user's breathing vibration signal in real time. When the breathing vibration signal is greater than a preset first threshold, the smart wearable device is determined to be in a first state, which is a standard wearing state. When the breathing vibration signal is less than the preset first threshold, the smart wearable device is determined to be in a second state. The wear detection method of this invention can significantly reduce the probability of false triggering of wear detection in smart wearable devices, thereby improving the user experience. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a schematic flowchart of a wear detection method provided in an embodiment of the present invention.

[0027] Figure 2 This is a schematic diagram illustrating the principle of processing respiratory vibration signals in a wear detection method according to an embodiment of the present invention.

[0028] Figure 3 This is a schematic diagram of a wear detection system provided in an embodiment of the present invention.

[0029] Figure 4 This is a schematic diagram of the internal structure of a smart wearable device that implements a wear detection method according to an embodiment of the present invention.

[0030] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0031] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0032] The technical solutions in the embodiments of this application will be clearly and thoroughly described below with reference to the accompanying drawings. In the description of the embodiments of this application, unless otherwise stated, the word "and / or" in the text is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone.

[0033] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. Furthermore, in the description of the embodiments of this application, "multiple" refers to two or more.

[0034] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0035] Example 1

[0036] Figure 1 The wear detection method is described in its entirety. Among other things, Figure 1 This is a schematic flowchart of a wear detection method provided in an embodiment of the present invention; the method can be executed by a system, which can be implemented by software and / or hardware.

[0037] like Figure 1 As shown, in this embodiment, the wear detection method includes steps S110 to S120.

[0038] The wear detection method is applied to a smart wearable device, which includes a nose pad.

[0039] The head-mounted device involved in this embodiment can be a pair of glasses including a speaker, a bone conduction microphone, and a nose pad; as an example, it can be smart glasses, and can also have communication functions, and be able to establish wired or wireless communication connections with electronic devices such as mobile phones and computers. For example, the wireless connection can be a short-range transmission technology such as wireless fidelity (Wi-Fi) or Bluetooth. The wired connection can be a universal serial bus (USB) connection, a high-definition multimedia interface (HDMI) connection, etc. This embodiment does not limit the type of communication connection. The device can share call functions with other communication devices through the established communication connection, such as answering and making phone calls. The device can have a built-in SIM card to enable answering and making phone calls, giving it the function of a mobile communication device. When wearing this head-mounted device, users can conveniently make calls without holding other communication devices.

[0040] Not limited to smart glasses, the head-mounted device involved in the embodiments of this application can also be other head-mounted devices, such as those with augmented reality (AR) or virtual reality (VR) capabilities.

[0041] This application does not limit the scope of head-mounted display devices, smart helmets, or head-mounted (head-mounted) headphones that utilize technologies such as virtual reality (VR), extended reality (XR), or mixed reality (MR).

[0042] A bone conduction VPU (Voice Pick-up Sensor) is a uniaxial accelerometer that utilizes piezoelectric material technology. It is primarily used to sense vocal cord movement, thereby capturing sound. When sound is conducted through the human skeleton, the sound signal causes minute mechanical vibrations in the bones. These vibrations can be captured by a sensitive contact sensor and converted into electrical signals. Bone conduction microphone technology converts sound into mechanical vibrations of different frequencies, capturing sound by detecting these minute vibrations of the facial bones. It does not rely on air as a transmission medium and offers advantages such as strong noise immunity and comfortable wear, playing a crucial role in voice communication in noisy environments.

[0043] Taking AR glasses as an example of a smart wearable device, the glasses include two temples and a nose pad. The nose pad is located in the middle of the two frames. The two temples are respectively positioned on the user's left and right ears to support the glasses. The nose pad is placed on the user's nose bridge to ensure the glasses are in a proper position. A bone conduction microphone can be located on the nose pad of the frame; this embodiment does not impose any limitations as long as the bone conduction microphone is positioned on the inner wall facing the wearer's nose bridge, allowing it to contact the wearer's nose bridge skin. In some specific embodiments, the lenses in the frame can be optical lenses, displays, or projection devices. The smart wearable device can collect the user's speech information through the microphone, and parse it to generate control commands or send them to other electronic devices for voice communication.

[0044] The smart wearable device may also include a speaker for converting audio electrical signals into sound signals. The smart wearable device can listen to music or make hands-free calls through the speaker. Additionally, one or more other sensors may be provided on the smart wearable device, including but not limited to pressure sensors, touch sensors, inertial measurement units (IMUs), and capacitive sensors. These can be configured by the designer according to the practical scenario and user needs; this embodiment does not impose any limitations in this regard.

[0045] The states of smart wearable devices can be categorized into standard wearing state, non-standard wearing state (within the non-wearing state), and removed state (within the non-wearing state). Specifically: Standard Wearing State: This refers to the smart wearable device being correctly worn by the user and functioning normally. Non-Standard Wearing State: This is a subset of the non-wearing state, referring to situations where the smart wearable device is on the user but not correctly worn or is not functioning normally. For example, the device may be partially detached or incorrectly positioned, resulting in limited functionality. Removed State: This refers to the smart wearable device being actively removed by the user and remaining in this removed state for a certain period of time.

[0046] S110. Real-time acquisition of the user's breathing vibration signal using a bone conduction microphone; wherein, the bone conduction microphone is mounted on the nose pad.

[0047] Taking AR glasses as an example, specifically, the human breathing rate is typically between 12 and 100 breaths per minute, with a normal breathing rate of approximately 30 to 40 breaths per minute, corresponding to a vibration signal at a frequency of 0.5 Hz. When AR glasses are worn on the user's face, the bone conduction microphone at the nose pad can detect the weak vibration signal caused by nasal breathing. By dynamically acquiring respiratory vibration data corresponding to breathing through the bone conduction microphone, feature extraction is performed on the respiratory vibration data to obtain its data features, which are then input into a pre-trained respiratory vibration recognition model.

[0048] In practical implementation, the bone conduction microphone collects the user's respiratory vibration signals. These signals are continuous analog electrical signals, while the respiratory vibration recognition model of this invention is based on digital data for computation and analysis. Therefore, to enable the respiratory vibration recognition model to effectively process the signals captured by the bone conduction microphone, the user's respiratory vibration signals must first be converted into digital form. Thus, before inputting these analog signals into the respiratory vibration recognition model for feature extraction and analysis, a preprocessing step using an analog-to-digital converter (ADC) is required. This ADC process converts analog signals into digital signals, enabling the recognition model to accurately analyze and extract features from the respiratory vibration data. Through this conversion, the model can more effectively process the digitized respiratory vibration signals, thereby achieving accurate recognition of the user's breathing pattern.

[0049] To enhance the applicability and versatility of the respiratory vibration data recognition model, this invention employs a comprehensive data acquisition method. Specifically, respiratory vibration audio data from a wide range of users, encompassing different genders and age groups, was collected using a bone conduction microphone. The collected data included audio information under various wearing conditions (such as tight, loose, and standard wear) and diverse real-world scenarios (such as quiet environments, noisy environments, whispered conversations, loud talking, silence, eating, etc.). Furthermore, the collected data included both instances where users consciously breathed to activate the smart wearable device's control functions and instances where users did not actively intend to breathe. This data served as a critical training set for training the respiratory vibration recognition model, ensuring that the model can accurately identify users' respiratory vibration signals under various real-world usage conditions.

[0050] After acquiring the user's respiratory vibration signal in real time using the bone conduction microphone, the method further includes: filtering the respiratory vibration signal to remove respiratory vibration signals with frequencies higher than 10 Hz. Filtering refers to removing noise components and unnecessary frequency components from the signal using a filter, retaining only the signal related to respiratory vibration characteristics. In this embodiment, an appropriate digital filter can be rotated to weaken or eliminate high-frequency noise, DC offset, and other interference, thereby improving signal quality and the accuracy of subsequent analysis. In the scenario of acquiring respiratory vibration signals using a bone conduction microphone in this embodiment, low-pass filtering can be used. Low-pass filtering can remove or weaken high-frequency components in the signal, retaining and highlighting the main content of the speech signal, primarily the fundamental frequency and envelope information of the speech. Speech signals are mainly concentrated in the lower frequency range, therefore low-pass filtering helps to eliminate noise (such as hissing, high-frequency howling, etc.) and other unnecessary high-frequency interference, while maintaining the intelligibility of the speech. Various relevant parameter values ​​and filtering methods can be selected during low-pass filtering. The low-pass filtered data can also be used as the speech data recorded by the bone conduction microphone.

[0051] After filtering and preprocessing the respiratory vibration signal, the process further includes signal amplification. That is, the signal first passes through a filtering and preprocessing module to remove high-frequency noise components, and then is amplified by a power amplifier (PA) for further analysis. In scenarios where respiratory vibration signals are acquired using a bone conduction microphone, the filtered signal can be amplified by 100dB.

[0052] In practice, the preprocessing process, in addition to filtering and amplification, may also include audio signal preprocessing operations such as framing, windowing, and normalization.

[0053] Framing refers to dividing a long, continuous digital signal into short, short segments (frames). This is because many characteristics of audio signals are relatively stable over short periods of time, and framing allows for analysis of each individual frame.

[0054] Windowing refers to adding a window function, such as a Hamming window, Blackman window, etc., to both ends of each frame obtained from framing before processing it. The purpose of windowing is to reduce frame boundary effects, making the transition of the signal between frames smoother, thereby improving the accuracy and stability of spectrum analysis.

[0055] Normalization refers to standardizing the data of each frame so that the signal amplitude falls within a specific range (e.g., -1 to 1, or 0 to 1), ensuring comparability between different frames and also facilitating numerical stability during algorithm training and recognition. It's worth noting that normalization methods include maximum-minimum normalization and mean-variance normalization.

[0056] In practical implementation, features can be extracted from respiratory vibration recognition training data using methods such as principal component analysis, short-time Fourier transform, time-frequency analysis, Mel frequency cepstral coefficients (MFCCs), and deep learning feature extraction. A machine learning model is a mathematical structure or algorithm that learns and infers useful information from input data, thereby predicting or making decisions about new data. In the field of machine learning, models are built by training on existing data. This training process involves optimizing model parameters to best fit the training data and to demonstrate good generalization ability on unknown data. In this implementation, the preset machine learning model can be a logistic regression model, decision tree, random forest, support vector machine, or deep learning model—a machine learning model suitable for classification and recognition tasks.

[0057] In summary, because all external factors such as contact, collision, picking up the glasses, or shaking the glasses cause the bone conduction microphone to capture instantaneous high-frequency signals, these signals typically exceed 1000 Hz. These high-frequency signals can be effectively filtered out using a 10 Hz low-pass filter in the preprocessing module. The signal is then amplified by 100 dB and a breathing vibration signal recognition model is used to identify waveforms with frequencies below 2 Hz. This processing flow accurately determines the wearing status of the smart wearable device.

[0058] S120. When the breathing vibration signal is greater than a preset first threshold, the smart wearable device is determined to be in a first state; the first state is a standard wearing state; when the breathing vibration signal is less than the preset first threshold, the smart wearable device is determined to be in a second state.

[0059] Figure 2 This is a schematic diagram illustrating the principle of processing respiratory vibration signals in a wearable detection method according to an embodiment of the present invention. Figure 2 As shown, the waveform curve of the preprocessed respiratory vibration signal is further analyzed using a respiratory vibration detection algorithm to determine the wearing status. Specifically, the analysis focuses on waveforms below 2Hz in the acquired respiratory vibration signal waveform curve.

[0060] When the breathing vibration signal is greater than a preset first threshold (amplitude 0.5V), or when a rhythmic 1 / 2 waveform is detected, it is determined that the user of the smart wearable device is wearing it.

[0061] The smart wearable device is correctly worn by the user and is in normal working condition. As an improvement in this embodiment, after determining that the smart wearable device is in the first state, the control module in the smart wearable device controls the speaker in the smart wearable device to emit audio signals and / or controls the smart wearable device to receive voice call signals. In specific implementations, functions such as video recording, photo taking, navigation, heart rate monitoring, blood pressure and blood oxygen detection, and exercise detection can also be triggered. These functions can be set by designers according to practical scenarios and user needs; this embodiment does not impose any restrictions on this. Such a setting can improve the intelligence level of the smart wearable device, eliminating the need for user input and improving ease of use.

[0062] Taking triggering a call function as an example, after determining that the smart wearable device is in the first state, the call function can be triggered based on the acquired first wearing information. Specifically, this can be done by first determining that the smart wearable device is in a standard wearing state, and then controlling the smart wearable device to enter a state where it can make phone calls. The call function can be implemented through a communication connection between the smart wearable device and a mobile terminal. The mobile terminal and the smart wearable device can communicate via wireless methods such as Bluetooth and Wi-Fi. The mobile terminal includes, but is not limited to, communication devices such as mobile phones or tablets. It should be noted that in some other embodiments, the smart wearable device can also be a device with independent communication capabilities. In this case, it is not necessary to send call request information to the mobile terminal; calls can be made through the dialing function and headset function of the smart wearable device.

[0063] Example 2

[0064] When the breathing vibration signal is less than a preset first threshold, the smart wearable device is determined to be in a second state. The second state is a non-wearing state. Figure 2 As shown, when the breathing vibration signal is less than a preset first threshold (amplitude 0.5V), or in other words, when the detected rhythmic waveform is less than 1 / 2, it is determined that the user of the smart wearable device is in a non-wearing state. The smart wearable device may also be in a non-standard wearing state within the non-wearing state, or in a removed state within the non-wearing state.

[0065] Example 3

[0066] When the breathing vibration signal is less than a preset first threshold and greater than a preset second threshold, the smart wearable device is determined to be in a third state; wherein, the third state is a non-standard wearing state. That is, when the breathing vibration signal is less than the preset first threshold (amplitude 0.5V) and greater than the preset second threshold (amplitude 0.1V), the smart wearable device is on the user, but is not worn correctly or is in an abnormal working state. For example, the device may be partially detached or incorrectly positioned, resulting in limited functionality. As an improvement to this embodiment, a prompting device can also output prompting information, which may specifically include one or more of indicator light prompts, sound prompts, and vibration prompts.

[0067] It should be noted that the weight of the glasses, the clamping force of the temples, and the fit of the nose pads will all cause differences in the signal picked up by the bone conduction microphone. In the specific implementation process, the designer can set these values ​​according to the practical scenario and user needs. This embodiment does not impose any restrictions on this.

[0068] Example 4

[0069] When the respiratory vibration signal is less than a preset second threshold (amplitude 0.1V), the smart wearable device is determined to be in a fourth state. When the duration of the smart wearable device in the fourth state exceeds a preset first time threshold, the control module in the smart wearable device controls the speaker to stop emitting audio signals and / or controls the smart wearable device to stop receiving voice call signals. The fourth state, the unworn state, refers to the state where the smart wearable device is actively removed from the user's body for an extended period. The first time threshold can be set to 2 minutes, 3 minutes, 4 minutes, 5 minutes, 8 minutes, 10 minutes, etc.; it can be set by the designer according to practical scenarios and user needs, and this embodiment does not impose any restrictions on this. In specific implementation, when the smart wearable device is determined to be in the unworn state, functions such as video recording, photography, navigation, heart rate monitoring, blood pressure and oxygen detection, and motion detection can be turned off. This can be set by the designer according to practical scenarios and user needs, and this embodiment does not impose any restrictions on this. This setting can improve the intelligence level of the smart wearable device, eliminating the need for user input and improving ease of use.

[0070] In summary, the wear detection method of the present invention is applied to a smart wearable device. It uses a bone conduction microphone mounted on the nose pad to collect the user's breathing vibration signals in real time. When the breathing vibration signal is greater than a preset first threshold, the smart wearable device is determined to be in a first state; the first state is a standard wearing state. When the breathing vibration signal is less than the preset first threshold, the smart wearable device is determined to be in a second state. The wear detection method of the present invention can significantly reduce the probability of false triggering of wear detection in smart wearable devices, thereby improving the user experience.

[0071] like Figure 3 As shown, this invention provides a wear detection system 300, which can be installed in an electronic device. Depending on the functions implemented, the wear detection system 300 may include a signal acquisition unit 310 and a wear status determination unit 320. The unit of this invention can also be called a module, which refers to a series of computer program segments that can be executed by the processor of an electronic device and perform a fixed function, and are stored in the memory of the electronic device.

[0072] In this embodiment, the functions of each module / unit are as follows:

[0073] To address the aforementioned issues, the present invention also provides a wearable detection system, which includes a signal acquisition unit 310 for real-time acquisition of the user's respiratory vibration signals using a bone conduction microphone; wherein the bone conduction microphone is mounted on the nose pad of the smart wearable device.

[0074] Wearing status determination unit 320 is used to determine that the smart wearable device is in a first state when the breathing vibration signal is greater than a preset first threshold; the first state is a standard wearing state;

[0075] When the breathing vibration signal is less than a preset first threshold, the smart wearable device is determined to be in the second state.

[0076] The wear detection system 300 of the present invention collects the user's breathing vibration signal in real time through the bone conduction microphone disposed on the nose pad; when the breathing vibration signal is greater than a preset first threshold, the smart wearable device is determined to be in a first state; the first state is a standard wearing state; when the breathing vibration signal is less than the preset first threshold, the smart wearable device is determined to be in a second state. The wear detection method of the present invention can greatly reduce the probability of false triggering of wear detection of smart wearable devices, thereby achieving the technical effect of improving user experience.

[0077] like Figure 4 As shown, the present invention also provides a smart wearable device 1 with a wear detection method.

[0078] The smart wearable device 1 may include a processor 10, a memory 11, and a bus, and may also include a computer program, such as a wear detection program 12, stored in the memory 11 and executable on the processor 10. The memory 11 may include both internal storage units of the wear detection system and external storage devices. The memory 11 can be used not only to store application software and various types of data, such as the code of the wear detection program, but also to temporarily store data that has been output or will be output.

[0079] like Figure 4 As shown, the present invention also provides a smart wearable device 1 that applies the wear detection method of the present invention.

[0080] The smart wearable device 1 may include a processor 10, a memory 11, and a bus, and may also include a computer program, such as a wear detection program 12, stored in the memory 11 and executable on the processor 10. The memory 11 may include both internal storage units of the wear detection system and external storage devices. The memory 11 can be used not only to store application software and various types of data, such as the code of the wear detection program, but also to temporarily store data that has been output or will be output.

[0081] The memory 11 includes at least one type of readable storage medium, such as flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the smart wearable device 1, such as the portable hard drive of the smart wearable device 1. In other embodiments, the memory 11 can be an external storage device of the smart wearable device 1, such as a plug-in portable hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the smart wearable device 1. Furthermore, the memory 11 can include both internal and external storage units of the smart wearable device 1. The memory 11 can be used not only to store application software and various types of data installed on the smart wearable device 1, such as the code of the wear detection program, but also to temporarily store data that has been output or will be output.

[0082] In some embodiments, the processor 10 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control unit of the electronic device, connecting various components of the entire electronic device through various interfaces and lines. It executes programs or modules (such as wear detection programs) stored in the memory 11, and calls data stored in the memory 11 to perform various functions and process data of the smart wearable device 1.

[0083] The bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This bus can be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable communication between the memory 11 and at least one processor 10, etc.

[0084] Figure 4 Only smart wearable devices with components are shown; those skilled in the art will understand that... Figure 4 The structure shown does not constitute a limitation on the smart wearable device 1, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0085] For example, although not shown, the smart wearable device 1 may also include a power supply (such as a battery) to power the various components. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management system, thereby enabling functions such as charging management, discharging management, and power consumption management through the power management system. The power supply may also include one or more DC or AC power supplies, a recharging system, a power fault detection circuit, a power converter or inverter, a power status indicator, or any other components. The smart wearable device 1 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0086] Furthermore, the smart wearable device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, a Bluetooth interface, etc.), which is typically used to establish a communication connection between the smart wearable device 1 and other electronic devices.

[0087] Optionally, the smart wearable device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), or a standard wired or wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the smart wearable device 1 and to display a visual user interface.

[0088] It should be understood that the embodiments described are for illustrative purposes only and are not limited to this structure in the scope of the patent application.

[0089] The wear detection program 12 stored in the memory 11 of the smart wearable device 1 is a combination of multiple instructions. When run in the processor 10, it can achieve the following: real-time acquisition of the user's breathing vibration signal using a bone conduction microphone; wherein the bone conduction microphone is set on the nose pad; when the breathing vibration signal is greater than a preset first threshold, the smart wearable device is determined to be in a first state; the first state is a standard wearing state; when the breathing vibration signal is less than the preset first threshold, the smart wearable device is determined to be in a second state.

[0090] Furthermore, the processor 10 can be used to call the wear detection program stored in the memory 11 and perform the following operations: the second state is the non-wearing state.

[0091] Furthermore, the processor 10 can be used to call the wear detection program stored in the memory 11 and perform the following operations: after the step of acquiring the user's breathing vibration signal in real time using the bone conduction microphone, the processor 10 further includes: performing filtering preprocessing on the breathing vibration signal to filter out breathing vibration signals with a frequency higher than 10 Hz.

[0092] Furthermore, the processor 10 can be used to call the wearing detection program stored in the memory 11 and perform the following operations: after the step of filtering and preprocessing the breathing vibration signal, it further includes: performing signal amplification processing on the breathing vibration signal.

[0093] Furthermore, the processor 10 can be used to call the wear detection program stored in the memory 11 and perform the following operations: when it is determined that the smart wearable device is in the first state, the processor controls the speaker in the smart wearable device to emit an audio signal and / or controls the smart wearable device to receive a voice call signal through the control module in the smart wearable device.

[0094] Furthermore, the processor 10 can be used to call the wear detection program stored in the memory 11 and perform the following operations: when the breathing vibration signal is less than a preset first threshold and greater than a preset second threshold, the smart wearable device is determined to be in a third state.

[0095] The third state is a non-standard wearing state.

[0096] Furthermore, the processor 10 can be used to call the wear detection program stored in the memory 11 and perform the following operations: when the breathing vibration signal is less than a preset second threshold, the smart wearable device is determined to be in the fourth state;

[0097] When the duration of the smart wearable device in the fourth state exceeds a preset first time threshold,

[0098] The control module in the smart wearable device controls the speaker in the smart wearable device to stop emitting audio signals and / or controls the smart wearable device to stop receiving voice call signals.

[0099] Furthermore, the processor 10 can be used to invoke the wear detection program stored in the memory 11 and perform the following operations: the first threshold is an amplitude of 0.5V, and the second threshold is an amplitude of 0.1V.

[0100] Specifically, the processor 10's implementation method for the above instructions can be found in [reference needed]. Figure 1 The descriptions of the relevant steps in the corresponding embodiments are not repeated here. Furthermore, if the modules / units integrated into the smart wearable device 1 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable medium may include: any entity or system capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0101] This invention also provides a computer-readable storage medium, which may be non-volatile or volatile, storing a computer program. When executed by a processor, the computer program performs the following: real-time acquisition of the user's respiratory vibration signal using a bone conduction microphone, wherein the bone conduction microphone is disposed on the nose pad; when the respiratory vibration signal is greater than a preset first threshold, the smart wearable device is determined to be in a first state; the first state is a standard wearing state; when the respiratory vibration signal is less than the preset first threshold, the smart wearable device is determined to be in a second state.

[0102] Specifically, the specific implementation method of the computer program when executed by the processor can be referred to the description of the relevant steps in the wear detection method of the embodiment, and will not be repeated here.

[0103] In the several embodiments provided by this invention, it should be understood that the disclosed devices, systems, and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0104] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0105] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0106] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0107] Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be embraced within the invention. No appended diagram markings in the claims should be construed as limiting the scope of the claims.

[0108] Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or systems stated in a system claim may also be implemented by a single unit or system through software or hardware. The term "second class" is used to indicate names and does not indicate any specific order.

[0109] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for detecting wearability, characterized in that, The wear detection method is applied to a smart wearable device, the smart wearable device including a nose pad; the wear detection method includes: The user's breathing vibration signals are collected in real time using a bone conduction microphone; wherein, the bone conduction microphone is mounted on the nose pad. When the breathing vibration signal is greater than a preset first threshold, the smart wearable device is determined to be in a first state; the first state is the standard wearing state. When the breathing vibration signal is less than a preset first threshold, the smart wearable device is determined to be in the second state.

2. The wearing detection method according to claim 1, characterized in that, The second state is the non-wearing state.

3. The wearing detection method according to claim 1, characterized in that, After acquiring the user's respiratory vibration signals in real time using the bone conduction microphone, the method further includes: The respiratory vibration signal is preprocessed by filtering to remove respiratory vibration signals with frequencies higher than 10 Hz.

4. The wearing detection method according to claim 3, characterized in that, After filtering and preprocessing the respiratory vibration signal, the process further includes: The respiratory vibration signal is amplified.

5. The wearing detection method according to claim 1, characterized in that, Once the smart wearable device is determined to be in the first state, the control module in the smart wearable device controls the speaker in the smart wearable device to emit audio signals and / or controls the smart wearable device to receive voice call signals.

6. The wearing detection method according to claim 1, characterized in that, When the breathing vibration signal is less than a preset first threshold and greater than a preset second threshold, the smart wearable device is determined to be in a third state. The third state is a non-standard wearing state.

7. The wearing detection method according to claim 6, characterized in that, When the breathing vibration signal is less than a preset second threshold, the smart wearable device is determined to be in the fourth state. When the duration of the smart wearable device in the fourth state exceeds a preset first time threshold, The control module in the smart wearable device controls the speaker in the smart wearable device to stop emitting audio signals and / or controls the smart wearable device to stop receiving voice call signals.

8. The wearing detection method according to claim 6, characterized in that, The first threshold is an amplitude of 0.5V, and the second threshold is an amplitude of 0.1V.

9. A wear detection system, characterized in that, The system includes: A signal acquisition unit is used to acquire the user's respiratory vibration signals in real time using a bone conduction microphone; wherein, the bone conduction microphone is mounted on the nose pad of the smart wearable device; The wearing status determination unit is used to determine that the smart wearable device is in a first state when the breathing vibration signal is greater than a preset first threshold; the first state is the standard wearing state. When the breathing vibration signal is less than a preset first threshold, the smart wearable device is determined to be in the second state.

10. A smart wearable device, characterized in that, The smart wearable device includes a memory, a processor, and a wear detection program stored in the memory and executable on the processor. When executed by the processor, the wear detection program implements the steps of the wear detection method as described in any one of claims 1 to 8.

11. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the wearing detection method as described in any one of claims 1 to 8.

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